Systems and Methods of Product Recognition Through Multi-Model Image Processing

4. The system of claim 1, wherein the second modeling technique comprises a barcode recognition modeling technique and the second image attribute comprises a barcode image attribute, wherein the decision control circuit is configured to process each frame of the series of frames by the barcode recognition modeling technique relative to the barcode image attribute, and obtain corresponding barcode product identification probabilities that the item, captured within each frame of the series of frames, is estimated to be the first product.

5. The system of claim 1, wherein the first modeling technique comprises optical character recognition (OCR) modeling technique and the decision control circuit in processing the at least one frame of the series of frames according to the first modeling technique is configured to process each frame of the series of frames by the OCR modeling technique relative to text image attributes, and obtain corresponding text product identification probabilities that the item, captured within each frame of the series of frames, is estimated to be the first product.

7. The system of claim 6, wherein the decision control circuit is configured to identify a threshold inconsistency between at least one of first product identification probabilities and one of second product identification probabilities, and apply at least one of a first weighting to at least one of the first product identification probabilities and a second weighting to at least one of the second product identification probabilities in response to identifying the threshold inconsistency.

8. The system of claim 6, wherein the decision control circuit, in applying the second weighting to the second product identification probabilities, is configured to identify in each frame of the series of frames a number of textual words present on the item and multiply the number of textual words by a word multiplier in defining the second weighting.